TRANSFORMATION OF UNIVERSITY DIDACTICS IN THE ERA OF ARTIFICIAL INTELLIGENCE: NAVIGATING LEARNING

Abstract

The rapid advancement of artificial intelligence technologies has become one of the key factors transforming contemporary higher education systems and reshaping traditional models of university didactics. The integration of AI-supported educational technologies, including generative artificial intelligence, adaptive learning systems, intelligent tutoring platforms, and automated educational support tools, has significantly changed the organization of teaching and learning processes within universities. In this context, the concept of learning navigation has gained increasing importance, reflecting students’ ability to independently manage educational trajectories, critically evaluate AI-generated information, and adapt to digitally mediated learning environments. The present study investigates the transformation of university didactics in the era of artificial intelligence and examines the role of learning navigation within higher education institutions in Kazakhstan. The study aims to analyze how artificial intelligence influences academic autonomy, learning motivation, digital literacy, and pedagogical interaction in university education. Particular attention is devoted to the empirical examination of students’ and academic staff’s perceptions regarding AI-supported educational practices and the transformation of teaching models in the context of digitalization. The research is grounded in constructivist and learner-centered educational approaches emphasizing active knowledge construction, self-regulated learning, and personalized educational pathways. A quantitative research design was employed using a structured questionnaire developed on the basis of international studies related to artificial intelligence in education, digital pedagogy, and educational technology adoption. The empirical study involved 312 respondents, including undergraduate students, master’s students, doctoral students, and university instructors from higher education institutions in Kazakhstan. Data collection was conducted between February and April 2026 through online survey distribution. The collected data were analyzed using SPSS Version 29 with the application of descriptive statistics, reliability analysis, Pearson correlation analysis, independent samples t-test, and multiple regression analysis. The findings demonstrated that artificial intelligence technologies are actively integrated into academic learning practices within universities in Kazakhstan. The majority of respondents reported frequent use of AI-supported tools for information retrieval, academic writing assistance, educational organization, and personalized learning support. The results revealed generally positive attitudes toward AI integration, particularly regarding flexibility of learning, access to educational resources, and enhancement of academic autonomy. Significant positive relationships were identified between AI usage, learning navigation, digital literacy, academic autonomy, and learning motivation. The regression analysis further confirmed that AI usage significantly predicts learning motivation and students’ ability to independently navigate educational environments